This paper presents a method for gathering and evaluating user attitudes towards previously released video games. A three-part video game franchise was selected, and all user reviews of these games were collected. The most frequently mentioned words of the game were derived from this dataset through word frequency analysis. The words, called “aspects” were then further analyzed through a manual aspect based sentiment analysis. The final analysis show that the rating of user review to a high degree correlate with the sentiment of the aspect in question. This knowledge is valuable for a developer who wishes to learn more about previous games success or failure factors.
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